Modelling vegetation management treatments with the Tree and Stand Simulator
Bibliographic record
Abstract
The Tree and Stand Simulator (TASS) has been used for over 20 years in British Columbia to generate yield tables for managed stands. In order to explore the impacts of weed control on site productivity we chose two vegetation management research trials where 10- to 15-year post-treatment data were available (Boston Bar and Mica research sites). Tree survival and height growth results were used to adjust the TASS input parameters to simulate the various brushing treatments. At the Boston Bar site, all vegetation reduction treatments shortened the Douglas-fir (Pseudotsuga menziesii var. glauca [Beissn.] Franco) physical rotation age by up to 10 years and culmination mean annual increment (cMAI) was increased 8% to 11% relative to the untreated control. At the Mica site, the glyphosate and all repeated manual cutting treatments resulted in a shortening of the Engelmann spruce (Picea engelmannii Parry) rotation age by seven years and increased cMAI by approximately 11% to12%. Key words: growth and yield modelling, vegetation management, Pseudotsuga menziesii, Picea engelmannii
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".